Sagar Zawar090220244008

Q 1

Pelican Stores

1. Descriptive statistics for all customers are shown followed by the same descriptive statistics for 4 subgroups of customers.

Net Sales (All Customers)    Mean   $77.60Median   $59.71Std. Dev. $55.66  Range   $274.36Skewness 1.715  

NET SALES BY CUSTOMER TYPE

 Married

Single

Regular

Promotion

Mean $78.03 $77.04 $61.99 $85.25Median 59 69 51 63.64Std.Deviation 57.67 46.21 35.07 61.38Range 274.36 163.3 137.25 274.36Skewness 1.732 1.254 1.351 1.52

A few observations can be made:a. Customers taking advantage of the promotional coupons spent more money on average. The meanamount spent by all customers is $77.60; the average amount spent by promotional customers was$85.25.b. The standard deviation of sales is $55.66. This indicates a fairly wide variability in purchaseamounts across customers. This variability is quite a bit smaller for the regular customers.

2  Crosstabulation of type of customer versus net sales is shown.

Net Sales

Customer0-25

25-50

50-75

75-100

100-125

125-175

175-200

200-225

225-250

250-275

275-300

Total

Promotional 7 17 17 8 9 3 2 3 1 2 1 70Regular 2 13 8 2 3 1 1 30Total 9 30 25 10 12 4 3 3 1 2 1 100

   From the cross tabulation it appears that net sales are larger for promotional customers. 

3. A scatter diagram of net Sales vs. age is shown below. A trend line has been fitted to the data. From this, it appears that there is no relationship between net sales and age.

Age is not a factor in determining net sales.

4. What is the relationshop between age and net sales for regular and for promotional customers?

We will first sort the data for Regular and Promotional customers

Correlation coefficient for

promotional= -0.10

Correlation coefficient for

regular= 0.25

These are low correlation values

Correlation for promotional is negative which means there is inverse relationship between age and net sales for promotional

Correlation for regular is negative which means there is direct relationship between age and net sales for regular

However, these correlationship values are low which means that the relationship may not be significant

Q 2

T-test: Independent Samples t-test – two groups & cut point(Dataset: 216data.sav) With the given dataset & 5% level of significance,

1.Get “Group Statistics Table” showing number of older siblings per section (10 & 11)

2.With “Independent Samples Test Table” what can you infer/conclude about number of older siblings per section are same or different?

10 20 30 40 50 60 70 80 900.00

50.00

100.00

150.00

200.00

250.00

300.00

350.00

Age

Net

Sal

es

T-Test

Group Statistics

Section N Mean Std. Deviation Std. Error Mean

Number of Older Siblings 10 14 .86 1.027 .275

11 32 1.44 1.318 .233

From the above group statistics table we can conclude that number of students having older siblings are different. Number of students in section 10 having older siblings are 14

and number of students in section 11 having older siblings are32. Students in section 10 have an average .86 older siblings and students in section 11 have an average 1.44

older siblings.

Independent Samples Test

Levene's Test for Equality of

Variances t-test for Equality of Means

95% Confidence Interval of the

Difference

F Sig. T df Sig. (2-tailed) Mean Difference

Std. Error

Difference Lower Upper

Number of Older Siblings Equal variances assumed 1.669 .203 -1.461 44 .151 -.580 .397 -1.381 .220

Equal variances not

assumed

-1.612 31.607 .117 -.580 .360 -1.314 .153

We can make a null hypothesis that number of students having number older siblings in section 10 and 11 have equal variances and the alternate hypothesis is the variances are

not equal. The level of significance is 5% (0.05). Levene’s test for equality of variances shows that the p value is .203 which is greater than than 0.05 so independent samles

test proves that we can accept null hypothesis or we fail to reject null hypothesis. The second part of independent samples test table shows that p value ( sig. 2- tailed) is .151

which is greater than 0.05. It implies that mean of number of students having older siblings in section 10 and 11 is same.

3.Get “Group Statistics Table” showing number of older siblings having more than and less than GPA 4.0

4.With “Independent Samples Test Table” what can you infer/conclude about number of older siblings having lower and higher are same or different?

T-Test

Group Statistics

Grade Point

Average N Mean Std. Deviation Std. Error Mean

Number of Older Siblings >= 4.00 2 2.50 .707 .500

< 4.00 44 1.20 1.250 .188

From the above group statistics table we can conclude that number of students having GPA greater than or equal to 4.00 are 2 and number of students having GPA less than

4.00 are 44. Number of students having GPA greater than or equal to 4.00 have an average 2.50 older siblings and students having GPA less than 4.00 have an average 1.20

older siblings.

Independent Samples Test

Levene's Test for Equality of

Variances t-test for Equality of Means

95% Confidence Interval of the

Difference

F Sig. t df Sig. (2-tailed) Mean Difference

Std. Error

Difference Lower Upper

Number of Older Siblings Equal variances assumed 1.184 .282 1.445 44 .156 1.295 .897 -.511 3.102

Equal variances not

assumed

2.424 1.304 .200 1.295 .534 -2.694 5.285

We can make a null hypothesis that number of students having GPA greater than or equal to 4.00 and students having GPA less than 4.00 have equal variances and the

alternate hypothesis is the variances are not equal. The level of significance is 5% (0.05). Levenes’s test for equality of variances shows that the p value (sig.) is .282 which is

greater than 0.05 so independent samples test proves that we can accept null hypothesis or we fail to reject null hypothesis. The second part of independent samples test table

shows that the p value (sig.2 tailed) is .156 which is greater than 0.05 which implies that the mean of number of students having GPA greater than or equal to 4.00 and number

of students having GPA less than 4.00 is same.

T-test: One-Way ANOVA (Dataset: 216data.sav)

Using One-Way ANOVA test for given dataset & 5% level of significance, test if you don’t want Psychology as major subject, which of the left over options/majors you will

choose out of Maths, English, Visual Arts or History? Note that GPA factor also affects this choice.

Oneway

ANOVA

Grade Point Average

Sum of Squares df Mean Square F Sig.

Between Groups .326 1 .326 1.161 .287

Within Groups 12.341 44 .280

Total 12.667 45